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An integrated approach to concept evaluation in a new product development

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  • Zeki Ayağ

    (Kadir Has University)

Abstract

A new product development (NPD) process can be thought as a comprehensive process in which the design is progressively detailed through a series of phases. At the end of each phase a design review is held to approve the design and release or not it to the next level. As one of these phases, concept selection aiming to select the most appropriate concept for further development, is conducted earlier in the process. As the further development progresses on a selected concept, it becomes more difficult to make design changes in terms of cost and schedule dimensions, and therefore, selecting the best concept among a set of available alternatives has been an important issue for companies. On the other hand, in the presence of many alternatives and selection criteria, the selection problem becomes a multiple-criteria decision making concept selection problem. To solve this problem, in this work, an integrated approach bringing two popular methods together: the modified technique for order preference by similarity to ideal solution (TOPSIS) and the analytical network process (ANP). The ANP method is used to determine the relative weights of a set of quantitative and qualitative evaluation criteria, as the modified TOPSIS method utilized to rank competing concept alternatives. In addition, a real example is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers.

Suggested Citation

  • Zeki Ayağ, 2016. "An integrated approach to concept evaluation in a new product development," Journal of Intelligent Manufacturing, Springer, vol. 27(5), pages 991-1005, October.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:5:d:10.1007_s10845-014-0930-7
    DOI: 10.1007/s10845-014-0930-7
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    References listed on IDEAS

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    Cited by:

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    2. Kheybari, Siamak & Rezaie, Fariba Mahdi & Farazmand, Hadis, 2020. "Analytic network process: An overview of applications," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    3. Habib Zare Ahmadabadi & Fatemeh Zamzam & Farahnaz Rahmani Meybodi & Dalia Streimikiene & Abbas Mardani, 2018. "Developent of a New Sesame Product using QFD and DOE methods: A Case Study of Sesame Product in Yazd," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 14(1), pages 27-44.
    4. Hamid Reza Fazeli & Qingjin Peng, 2023. "Integrated approaches of BWM-QFD and FUCOM-QFD for improving weighting solution of design matrix," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1003-1020, March.
    5. C. K. H. Lee, 2019. "A knowledge-based product development system in the chemical industry," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1371-1386, March.
    6. Tien-Li Chen & Chin-Chuan Chen & Yen-Ching Chuang & James J. H. Liou, 2020. "A Hybrid MADM Model for Product Design Evaluation and Improvement," Sustainability, MDPI, vol. 12(17), pages 1-22, August.

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